While AI stirs fear among the well-to-do, anticipating job losses, its potential in the developing world is largely unexplored and could be transformative. Going beyond the common fear of job displacement, AI's impact on lower-income countries could offer new possibilities, opening up avenues previously unimaginable. The challenge is to find appropriate applications, tailor existing tools, and manage risks.
AI: More than just a job threat
In the developed world, AI sparks fears of massive job displacement. But for lower-income countries, where a large share of the population works in sectors like agriculture that are less prone to automation, the focus isn't on AI replacing jobs but on how AI can be employed to open new possibilities. Instead of being a threat, AI could become a powerful tool to address challenges endemic to these regions, from poor access to quality education and healthcare to unreliable credit systems. The potential is enormous; the key is to identify and harness the most transformative applications.
The conversation around AI investment and regulation has predominantly focused on wealthy countries, which are the hub for tech companies and AI research. However, the impact of AI, both positive and negative, will play out differently in developing countries. The resources needed, the regulations to be implemented, and the investment landscape would need to be tailored to their unique circumstances. As we consider the future of AI, it is crucial that we turn our attention to developing an AI agenda that works for the developing world.
Machine learning's touch on the world's poor
Machine learning is already making a difference in the lives of the world’s poor. From creating alternative credit scores for those without financial histories to identifying the poorest households for targeted aid during crises, AI has shown its potential. Looking ahead, we could see AI-powered personalized tutors meeting the needs of students in remote schools or helping professionals upgrade their skills. AI might provide better and more widely available health diagnostics or offer support for mental health. And it could even assist entrepreneurs in navigating bureaucratic processes. The possibilities are immense.
Adapting and innovating AI tools
The two primary paths for AI tools in the developing world are adaptation and innovation. One approach is to adapt AI applications that work well in wealthy countries for use in poorer nations. For example, chatbot tutors developed for wealthy schools could be modified for remote schools in developing countries with poor internet connectivity. Alternatively, entirely new AI applications can be developed to meet the specific needs of the developing world. An AI-powered financial planner for subsistence farmers is one such example. The key is to think outside the box, considering the unique challenges and opportunities present in these countries.
The diffusion of AI presents unique risks for developing countries, which generally have less capacity to regulate the technology. Issues such as centralization, technological gaps, or socio-political problems like the risk of deepfakes in fragile political systems, present unique challenges. Developing countries may have to focus on adapting to new technology rather than wholly controlling it. This could involve focusing on regulating industries that use AI or ensuring consumers have adequate processes to report issues and appeal decisions. The key will be to manage risks while reaping the benefits the technology can offer.